Yue et al. in Health and Disease (2017) 16:120 DOI 10.1186/s12944-017-0491-9

RESEARCH Open Access The association of metabolism relative polymorphisms and ischemic stroke in Han and Uighur population of Xinjiang Yun-hua Yue1*, Ling-yun Liu1, Liang Hu1, You-mei Li1, Jie-ping Mao2, Xiao-ying Yang2 and Na-mu Dila2

Abstract Background: The present study is aimed to evaluate difference of lipid metabolism related gene single nucleotide polymorphisms (SNPs) with ischemic stroke (IS) in Han and Uighur population of Xinjiang, China. Methods: Four hundred eight patients with ischemic stroke and 347 unrelated healthy individuals of age and sex matched were genotyped for A5 (ApoA5), lipase (LPL), Cholesteryl ester transfer (CETP) and low-density lipoprotein receptor (LDL-R) . Their mutation difference was analyzed by SNaP shot techniques. GeneMapper4.1 SPSS20.0 software was used for data management and analysis. Using a single locus analysis, the distribution difference of genotype loci in ischemic stroke cases and controls were detected to assess the genetic risk factors of ischemic stroke. Results: Significance differences of genotype distribution in ischemic stroke cases and controls were observed in LDLR rs688 in Han and Uighur population in recessive model from analysis of single gene locus. It also was found that dramatic difference of (TG) of LPL rs328 and systolic blood pressure in CETP rs708277 of total population. In binary logistic regression analysis of total studied population, ischemic stroke was observed significantly associated with LDLR rs688 both addictive model (TT/CC, adjusted OR = 1.47, 95% CI = 1.04–2.07) and recessive model (TT/CT + CC, adjusted Odds ratio (OR) = 2.66, 95% Confidence Interval (CI) = 1.37–5.14). In Han population, ischemic stroke was observed significantly associated with rs688 both in addictive model (TT/CC, adjusted OR = 3.27, 95% CI = 1.06–10.05). In Uighur population, no significant association was found between gene polymorphisms and the risk of ischemic stroke. Combined analysis of multiple gene and loci, interaction effects of LDLR rs688 C/T, ApoA5 rs662799 A/G and CETP rs708272 C/T denoted a significant influence on IS susceptibility. Conclusion: Single nucleotide polymorphisms of lipid metabolism relative gene were significantly associated with the morbidity of ischemic stroke in Han population. The interaction effects of rs688 C/T with ApoA5 rs662799 A/G and CETP rs708272 C/T promoted the occurrence of IS. Keywords: Apolipoprotein, Low density lipoprotein receptor, Ischemic stroke, Single nucleotide polymorphism

* Correspondence: [email protected] 1Department of Neurology, Yangpu Hospital Tongji University School of Medicine, No. 450 Tengyue Road, Shanghai 200090, China Full list of author information is available at the end of the article

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Yue et al. Lipids in Health and Disease (2017) 16:120 Page 2 of 8

Background of Neurology of the Youyi Hospital of Wulumuqi from Stroke is one of the leading causes of death over the all July 2010 to July 2012. Three hundred forty-seven age and world and cause major health problem [1]. However, it sex matched unrelated healthy individuals also were is the first cause of morality in China [2]. Ischemic included in this study as a control The inclusion and stroke (IS) frequently caused dysfunction of the brain exclusion criteria for ischemic stroke were determined as and comprises 80% of cases [3]. The reasons for the our previous described [18]. The hypertension and patho-physiological cause of ischemic stroke are unclear. Diabetes mellitus (DM) diagnosis criteria were described as The concept was widely accepted that stroke is caused our and the other lab [18, 19]. Briefly, blood pressure (BP) by combination of genetic and environment factors. was measured at routine method. The second BP with the Among genetic factors, it well known that a few specific fifth-phase diastolic pressure was used for analysis. Diabetes gene variants of lipid metabolism are modifiable risk mellitus (DM) was classified as fasting plasma glucose factors for the occurrence of IS [1, 4]. The extensive (FPG) ≥7.0 mmol/L and/or 2 h plasma glucose (PG) study indicated that atherosclerotic plaques form is the ≥11.1 mmol/L or already diagnosed as diabetes patients. To major cause of IS [5, 6], which the occurrence of athero- assess the relationship of hypertension and DM with dislipi- sclerotic plaques are strongly associated with abnormal demia, the lipid level in IS patients with hypertension and lipid metabolism [7, 8]. So far, it was known that Apolipo- DM was evaluated. This study protocol was approved by protein A5 (ApoA5), (LPL), Cholesteryl the Youyi hospital ethics committee and all participants ester transfer protein (CETP) and low-density lipoprotein weregivensignedinformedconsent. receptor (LDL-R) gene mutations had increased the concentration of lipids [9–11]. DNA extraction The association of human candidate genes with IS 5 ml of peripheral whole blood was collected in an EDTA patients may be the confounding effects of ethnic, envir- coated vacutainerand blood samples were stored at 4 °C onment factor and individual life style [12]. Xinjiang re- before DNA extraction. The genomic DNA was isolated gion of China lies in the north-west part of the mainland using Qiagen DNA mini isolation kit. All procedure was and the weather is dry and cold. There is a high altitude performed according to kit description. DNA concentra- in this area and relative lack of oxygen. Furthermore, the tion and purity were determined by Nano Drop 2000 Uighur population has different risk factors of ischemic machine (Thermo Scientific, USA). stroke than Han population because of the ethnicity, genetic background and lifestyle. The most population Selection of SNP candidate genes in Xinjiang had more caloric food and alcoholic intake To identify the most likely relative lipoprotein SNP candi- [13, 14]. Hu et al. reported that the risk of dyslipidemia date genes, we accessed to http://www.ncbi.nlm.nih.gov/ in CETP rs708272 CC of Uighur residents was much SNP database and selected APOA5, LPL, CETP and LDLR higher that rs708272 CT or TT genotype [15]. Quan genes asour candidate genes association with acute IS. et al. found that the patients with impaired fasting glucose (IFG) in Uighur population had more risk for Genotyping of the ApoA5, LPL, CETP and LDLR gene SNPs dyslipidemia than Han population with IFG [16]. Li et al. DNA sample were analyzed by SNaPshot SNP typing showed that the level of hypercholesterolemia in Kazakh machine (SnaPshot multiplex, ABI, USA). Detail PCR and population of Xinjiang was significant higher than it in single-base extension primer sequences were recorded as Uygur and Han [17]. These data indicated that different our previous study [18]. genetic background had more effect on their serum lipids level. Therefore, we determined to investigate Statistical analysis ApoA5, LPL, CETP and LDLR gene single nucleotide The statistical analysis was performed using SPSS polymorphisms (SNPs) in Han and Uighur population of 20.0(IBM, USA). Clinical parameter such as serum TC, Xinjiang region because of their different ethnicity, TGL, HDL-C, LDL-C, ApoA1, ApoB, Lpa glucose, and genetic, environment factors background and life style. serumwere measured with automatic machine in IS These results will provided a unique link between the patients and controls. The allelic frequencies were relationships the lipid metabolism related gene SNP with calculated by Hardy-weinberg equipment method. Multi- the occurrence of IS. variate logistic regression analyses were performed for genotype, allele frequencies and lipid profile factor associ- ated with ischemic stroke. Through counting DNA se- Methods quencing data, the genotype and allele frequencies can be Study subjects estimated. The distinction between studied groups were Patients with ischemic stroke of 250 Han and 158 analyzed by Pearson’sX2 test. Then, logistic regression Uighur population and were enrolled from Department analysis was measured the strength. Yue et al. Lipids in Health and Disease (2017) 16:120 Page 3 of 8

Table 1 Candidate genes and SNP information Table 3 Hardy-Weinberg equilibrium test of Overall sample Gene IS group Control group P case group (n = 408) (n = 347) SNP A1 A2 AN EN χ2 P Age (year-old) 61.9 ± 11.8 61.8 ± 11.7 0.916 Rs662799 G A 30/153/225 28/157/223 0.263 0.877 Sex (Male/Female, N) 242/166 201/146 0.943 Rs320 G T 12/121/275 13/119/276 0.114 0.945 BMI (kg/m2) 24.2 ± 3.3 23.9 ± 4.1 0.542 Rs328 G C 1/58/349 2/56/350 0.574 0.768 Hypertension (N, %) 281(68.9) 129(37.2) <0.001 Rs708272 A G 81/196/131 79/201/129 0.204 0.903 DM (N, %) 129 (31.6) 46(13.3) <0.001 Rs688 T C 40/130/238 27/156/225 11.344 0.003 TC (mmol/L) 4.85 ± 1.08 4.47 ± 1.01 <0.001 SNP single nucleotide polymorphism, AN Actual number, EN TG (mmol/L) 1.71 ± 0.65 1.51 ± 0.66 <0.001 Expectable number LDL-C (mmol/L) 3.28 ± 0.61 2.46 ± 0.63 <0.001 HDL-C (mmol/L) 1.06 ± 0.25 1.27 ± 0.26 <0.001 These mutations were verified by PCR and DNA product sequencing. These data confirmed that these candidate ApoA1 (g/L) 0.83 ± 0.22 1.03 ± 0.31 <0.001 genes were indeed mutated in IS patients. ApoB (g/L) 0.81 ± 0.22 0.95 ± 0.35 <0.001 Lpa (mg/L) 173.57 ± 53.17 123.81 ± 62.43 <0.001 The distribution difference of ApoA5 rs662799, LPL SNP single nucleotide polymorphism, BMI Body Mass Index, IS ischemic stroke, rs320, rs328, CETP rs708277, LDLR rs688 mutation with DM Diabetes mellitus, TC Total , TG , LDL-C low Density Lipoprotein-C, HDL-C High Density Lipoprotein-C, ApoA1 Apolipoprotein–A1, IS in Han and Uighur population by Hardy-Weinberg ApoB , Lpa lipoprotein a equilibrium test We compared the distribution difference of APOA5 Results rs662799, LPL rs320, LPL rs328, CETP rs708277 and Clinical character of subjects LDLR rs688 gene loci in IS and control Han and Uighur The basic clinical characteristics of the 408 IS patients population of Xinjiang. Then we calculated the differ- and 347 control were shown in Table 1. There were no ence in overall case and control group by Hardy- significant difference in age, sex and body mass index Weinberg equilibrium test. Data were shown in Tables 3 (BMI), However, it was greatly differences in hyperten- and 4. The frequencies of LDLR rs688 mutation were sion, diabetes mellitus (DM); Total Cholesterol (TC); dramatic increased in IS patients than the controls Triglycerides (TG); low Density Lipoprotein-C (LDL-C); (P = 0.003). This result strongly supports the association High Density Lipoprotein-C (HDL-C); Apolipoprotein– LDLR mutation with IS. However, there was no differ- A1 (ApoA1); Apolipoprotein B (ApoB); lipoprotein a ence that the frequencies of ApoA5 rs662799, LPL (Lpa) (P < 0.001). Therefore, these clinical parameters rs320, LPL rs328, CETP rs708272 in Hardy-Weinberg provide an evidence that IS patients often have abnormal equilibrium test. serum lipoprotein level. It also is closed association with hypertension and DM history. The distribution difference of ApoA5 rs662799, LPL rs320, rs328, CETP rs708277, LDLR rs688 mutation with IS and control according to their dominant, recessive and Lipidsmetabolism relative genes SNP information codominant genetic style by pearson χ2 and CHISP test After we accessed to http://www.ncbi.nlm.nih.gov/SNP The next, we compared the difference of ApoA5, database a, it was found that possible APOA5, LPL, CETP LPL, CETP and LDLR SNP mutation between Han and LDLR genes candidate SNP site were shown in Table 2. and Uighur IS patients and control by pearson χ2 test. The result were shown in Tables 5 and 6. By

Table 2 Candidate Genes and SNP information Table 4 Hardy-Weinberg equilibrium test of Overall sample Gene Locus Function Sites HF LF Reference CONTROL group ′ APOA5 rs662799 5 -flanking 116,663,707 A G 0.267(HCB) SNP A1 A2 AN EN χ2 P LPL rs320 19,819,077 T G NA(HCB) Rs662799 G A 25/110/212 18/123/205 4.320 0.115 rs328 Ser474Ter 19,819,724 C G 0.089(HCB) Rs320 G T 13/99/235 11/102/233 0.465 0.793 CETP rs708277 Intron 56,996,288 C T NA(HCB) Rs328 G C 1/58/349 2/56/350 0.574 0.768 LDLR rs688 Asn591Asn 11,227,602 C T 0.174(HCB) Rs708272 A G 82/160/105 76/173/99 1.817 0.403 SNP ApoA5 – LPL single nucleotide polymorphism, Apolipoprotein A5, Rs688 T C 14/129/204 18/121/208 1.495 0.474 lipoprotein lipase, CETP Cholesteryl ester transfer protein, LDLR Low density lipoprotein receptor, HF high frequency, LF low frequency, NA no answer, HCB SNP single nucleotide polymorphism, AN Actual number, EN Han, Chinese and Beijing Expectable number Yue et al. Lipids in Health and Disease (2017) 16:120 Page 4 of 8

Table 5 The distribution of different genotype of recessive between two Uighur groups SNP Recessive Case Control χ2 P Rs662799 GG:(GA + AA) 30/378 (7.4/92.6) 25/322(7.2/92.8) 0.006 0.938 Rs320 GG:(GT + TT) 12/396 (2.9/97.1) 13/334(3.7/96.3) 0.380 0.538 Rs328 GG:(GC + CC) 1/407(0.2/99.8) 3/344(0.9/99.1) NA NA Rs708272 AA:(GA + GG) 81/327 (19.9/80.1) 82/265(23.6/76.4) 1.581 0.209 Rs688 TT:(CT + CC) 40/368 (9.8/90.2) 14/333(4.0/90.6) 9.399 0.002 SNP single nucleotide polymorphism, N/A no answer contrast, either Uighur (Table 5) or Han population we detected major serum lipid levels, glucose, height, (data not shown) was highly significant when com- weight, BMI and blood Pressure with LPL rs328 and pared to respective controls in recessive genetic CETP.rs70877 in total population. Data were shown in model. However, associations were not significant in Tables 10 and 11. We found that there are significant dominant genetic model. Interest, this result also is lower TG in rs328 GG than in rs328 CC and GC popu- consistent by CHISP test (Tables 6 and 7). Further, lation (Table 10). Low SBP also was measured in no significant association was found in dominant CETP.rs70877 GA and AA (Table 11). and codominant genetic model in stroke cases (data These results indicated that different lipid protein not shown). metabolism relative gene SNPs is associated with special clinical profile. Association of ApoA5 rs662799, LPL rs320, rs328, CETP rs708277, LDLR rs688 mutation with IS in Han and Uighur Discussion population by binary logistic regression analysis The risk factors of stroke were extensively studied We further compared the difference of IS patients and con- [10, 20, 21]. Recent data revealed that a few protein trol by binary logistic regression analysis. It was observed genetic polymorphisms were significantly association significantly associated withrs688bothaddictivemodel with the risk for stroke [22–24]. Here, we investi- (TT/CC, adjusted OR = 1.47, 95% CI = 1.04–2.07, P <0.01) gated that ApoA5, LPL, CETP and LDLR gene poly- and recessive model (TT/CT + CC, adjusted OR = 2.66, morphisms in IS patients from Xinjiang region. The 95% CI = 1.37–5.14, p = 0.004) (Tables 8 and 9). In Han results provided linkage of different genetic background, population, ischemic stroke was observed significantly asso- life style and the occurrence of ischemic stroke. ciated with rs688 both in addictive model (TT/CC, adjusted Our study showed the presence of ApoA5 rs662799, OR = 3.27, 95% CI = 1.06–10.05, P < 0.05). In Uighur LPL rs320, LPL rs328(Ser474 Ter), CETP rs708277 population, no significant association was found between and LDLR rs688 in IS patients from Xinjiang region. genepolymorphismsandtheriskofischemicstroke(data Surprisingly, it was observed that rs688 genetic poly- not shown). Combined analysis of multiple gene and loci, morphism had significantly more difference in IS pa- interaction effects of LDLR rs688 C/T, ApoA5 rs662799 A/ tients than in control in recessive model analysis. This G and CETP rs708272 C/T denoted a significant influence phenomenon also was seen by binary logistic regression on IS susceptibility (p < 0.05). analysis of total studied population. IS patients was ob- served significantly associated with rs688 both addictive Association of LPL rs328 and CETP rs708277 with serum model (TT/CC, adjusted OR = 1.47, 95% CI = 1.04–2.07, lipid protein levels and clinical profile in total population P < 0.01) and recessive model (TT/CT + CC, adjusted To explore the association of lipid metabolism gene OR = 2.66, 95% CI = 1.37–5.14, p < 0.01). In Han popula- SNPs with serum lipid protein levels and clinical profile, tion, ischemic stroke was observed significantly associated

Table 6 The distribution of different genotype of recessive between two Han groups SNP Recessive Case Control CHISP P Rs662799 GG:(GA + AA) 21/229 (8.4/91.6) 19/179(9.6/90.4) 0.194 0.659 Rs320 GG:(GT + TT) 10/240 (4.0/96.0) 8/190(4.0/96.0) 0.000 0.983 Rs328 GG:(GC + CC) 1/249(0.4/99.6) 3/195(1.5/98.5) NA NA Rs708272 AA:(GA + GG) 49/201 (19.6/80.4) 49/149(24.7/75.3) 1.713 0.191 Rs688 TT:(CT + CC) 16/234 (6.4/93.6) 4/194(2.0/98.0) 4.970 0.036 SNP single nucleotide polymorphism, N/A no answer Yue et al. Lipids in Health and Disease (2017) 16:120 Page 5 of 8

Table 7 The distribution of different genotype of recessive between two Uighur groups SNP Recessive Case Control CHISP P Rs662799 GG:(GA + AA) 9/149 (5.7/94.3) 6/143(4.0/96.0) 0.460 0.718 Rs320 GG:(GT + TT) 2/156 (1.3/98.7) 5/144(3.4/96.6) 1.5030.220 Rs328 GG:(GC + CC) 0/158 (0.0/100.0) 0/149(0.0/100.0) NA NA Rs708272 AA:(GA + GG) 32/126 (20.3/79.7) 33/116(22.1/77.9) 0.165 0.685 Rs688 TT:(CT + CC) 24/134 (15.2/84.8) 10/139(6.7/93.3) 5.597 0.018 SNP single nucleotide polymorphism, N/A no answer with rs688 both in addictive model (TT/CC, adjusted ApoA5 had similar phenomenon like LDLR. It was re- OR = 3.27, 95% CI = 1.06–10.05, P < 0.05). However, This ported that ApoA5 T-1131C, T1259C, and IVS3 + G476A phenomenon weren’t observed in Uighur population. are associated with IS, DM and CAD [11, 25]. These It was well known that a single gene may have differ- SNPs result in high triglycerides. It also was widely ob- ent genetic polymorphism with different kind of served that some gene SNPs are closely associated with disease [25–28]. The same gene in one kind of dis- special clinical profile in Xinjiang. Our study indicated ease may have diverse SNPs owing to different race that SNPs of lipid metabolism relative genes is associ- and place. It was widely reported that LDLR genetic ated with response of drug [18] Zhang et al. reported polymorphisms are associated with many disease such that there are significant difference in β3-adrenergic as essential hypertension [28], receptors (ADRβ3) gene polymorphisms rs6986132 of (CAD) [29] and high cholesterol [30]. These SNP site Han and Uighur populations in Xinjiang. They also were C1773T, rs2228671, rs1122608 and so on. A observed the ADRβ3 rs2298423 G allele carriers similar study were reported that rs688 is associated increase risk for TC and LDL-C level in the Uighur with IS patients in Taiwanese population [24]. Gao populations of Xinjiang [31]. Abulizi et al. found that et al. revealed that rs688 increase exon12 alternative ApoA5 gene c553G-T polymorphism is associated splicing and affected LDL receptor function [27]. Zhu with high TG levels in Han and Uighur population et al. showed that rs688 promote a high serum chol- [32]. Our present data showed that LPL rs328 CC esterol by modulating LDLR exon12 splicing efficiency and GC allele people have high TG than rs328 GG al- [30]. Therefore, we speculated that rs688 firstly in- lele population. People of CETP rs708277 GG allele crease serum cholesterol and then cause atheroscler- had high SBP than it in rs708277 GA or AA allele otic plaques form. people.

Conclusion Table 8 Additive model analysis of different genes with stroke Our results indicated that SNPs of lipid metabolism SNP P OR (95% CI) relative gene is closely associated with different popu- Rs662799 0.205 Ref lation of Xinjiang. In Han population, ischemic stroke Rs662799 GA/AA 0.139 1.28 (0.92–1.79) was significantly associated with LPLR rs688 polymor- Rs662799 GG/AA 0.112 1.76 (0.88–3.54) phisms.However,thisphenomenondidn’t detect in Rs320 0.819 Ref Uighur population. We also found that different spe- Rs320 GT/TT 0.891 1.02(0.74–1.42) cial SNPs allele have different serum lipid and blood pressure levels. These results demonstrated that we Rs320 GG/TT 0.551 0.77(0.33–1.80) need take care of some specific SNPs people because Rs328 0.514 Ref they is easy to develop ischemic strokes. Rs328 GC/CC 0.744 0.93 (0.61–1.42) Rs328 GG/CC 0.264 0.27(0.03–2.67) Table 9 Recessive model analysis of different genes with stroke Rs708272 0.413 Ref SNP P OR (95% CI) Rs708272 GA/GG 0.695 0.93 (0.66–1.32) Rs662799 GG/(GA + AA) 0.745 1.10(0.62–1.96) Rs708272 AA/GG 0.195 0.76 (0.50–1.15) Rs320 GG/(GT + TT) 0.537 0.77(0.33–1.78) Rs688 0.013 Ref Rs328 GG(GC + CC) 0.268 0.28(0.03–2.69) Rs688 TC/CC 0.611 0.92(0.67–1.27) Rs708272 AA/(GA + GG) 0.204 0.79(0.55–1-13) Rs688 TT/CC 0.006 2.57 (1.31–5.03) Rs688 TT/(CT + CC) 0.004 2.66(1.37–5.14) SNP single nucleotide polymorphism, OR Odds ratio, CI confidence interval SNP single nucleotide polymorphism, OR Odds ratio, CI confidence interval Yue et al. Lipids in Health and Disease (2017) 16:120 Page 6 of 8

Table 10 Association comparison of rs328 genotype with stroke in study population Rs328 CC GC GG P n Mean ± SD n Mean ± SD n Mean ± SD Age 640 61.4 ± 12.61 111 64.4 ± 9.3 4 61.8 ± 12.9 0.052 Height 637 1.67 ± 0.08 111 1.66.1 ± 0.08 4 1.59 ± 0.065 0.058 Weight 638 68.80 ± 10.65 110 68.28 ± 11.39 4 58.75 ± 9.11 0.162 BMI 637 24.67 ± 2.89 110 24.78 ± 3.00 4 23.06 ± 92.30 0.499 SBP 640 138.49 ± 23.29 111 137.05 ± 24.52 4 122.50 ± 16.58 0.340 DBP 640 84.52 ± 42.64 111 81.50 ± 13.84 4 72.50 ± 6.46 0.642 Glucose 640 6.25 ± 3.13 111 6.20 ± 2.99 4 7.48 ± 5.45 0.725 TG 640 2.02 ± 1.24 111 1.70 ± 0.99 4 1.48 ± 0.30 0.026 TC 640 4.34 ± 1.15 111 4.33 ± 0.85 4 4.70 ± 0.6 1 0.806 HDL 640 1.19 ± 0.66 111 1.24 ± 0.84 4 1.32 ± 0.49 0.748 LDL 639 2.66 ± 0.86 111 2.63 ± 0.77 4 2.54 ± 0.32 0.926 APOA1 640 1.24 ± 0.32 111 1.23 ± 0.22 4 1.07 ± 0.23 0.514 APOB 640 0.90 ± 0.75 111 0.85 ± 0.33 4 0.99 ± 0.18 0.714 HCY 640 9.98 ± 7.29 111 8.69 ± 4.87 4 5.50 ± 2.54 0.094 TC/HDL-C 640 4.32 ± 2.10 111 4.08 ± 1.34 4 3.78 ± 0.798 0.452 LDL-C/HDL-C 639 2.68 ± 2.08 111 2.51 ± 1.04 4 2.15 ± 0.78 0.603 ApoB/ApoA1 640 0.77 ± 0.80 111 0.71 ± 0.34 4 0.97 ± 0.35 0.677 BMI Body Mass Index, SBP Systolic blood pressure, DBP diastolic blood pressure, TC Total Cholesterol, TG Triglycerides, LDL-C low Density Lipoprotein-C, HDL-C High Density Lipoprotein-C, ApoA1 Apolipoprotein–A1, ApoB Apolipoprotein B

Table 11 Association comparison of rs708272 genotype with stroke in study population Rs708272 GG GA AA P n Mean ± SD n Mean ± SD n Mean ± SD Age 236 61.0 ± 11.67 356 62.4 ± 11.7 163 62.0 ± 11.9 0.353 Height 236 1.67 ± 0.08 354 1.66.1 ± 0.08 162 1.67 ± 0.07 0.394 Weight 235 68.61 ± 10.51 355 68.59 ± 10.70 162 68.94 ± 11.33 0.937 BMI 235 24.49 ± 2.273 353 24.76 ± 2.86 163 24.78 ± 3.23 0.467 SBP 236 141.33 ± 23.96 356 136.78 ± 24.35 163 136.72 ± 20.18 0.046 DBP 236 88.74 ± 67.74 356 81.69 ± 13.74 163 85.26 ± 13.96 0.086 Glucose 236 6.06 ± 2.51 356 6.25 ± 2.87 163 6.51 ± 4.24 0.371 TG 236 2.01 ± 1.27 356 1.95 ± 1.18 163 1.95 ± 1.20 0.803 TC 236 4.34 ± 0.97 356 4.34 ± 1.18 163 4.35 ± 1.14 0.997 HDL 236 1.22 ± 0.739 356 1.19 ± 0.65 163 1.17 ± 0.58 0.738 LDL 236 2.64 ± 0.79 356 2.64 ± 0.82 163 2.70 ± 0.968 0.718 APOA1 236 1.24 ± 0.23 356 1.22 ± 0.23 163 1.27 ± 0.50 0.124 APOB 236 0.85 ± 0.28 356 0.92 ± 0.81 163 0.89 ± 0.86 0.507 HCY 236 9.81 ± 7.176 356 9.73 ± 6.93 163 9.78 ± 6.91 0.991 TC/HDL-C 236 4.21 ± 1.60 356 4.33 ± 2.40 163 4.25 ± 1.53 0.757 LDL-C/HDL-C 236 2.59 ± 1.12 356 2.71 ± 2.59 163 2.63 ± 1.18 0.730 ApoB/ApoA1 236 0.71 ± 0.28 356 0.80 ± 0.87 163 0.76 ± 0.92 0.387 BMI Body Mass Index, SBP Systolic blood pressure, DBP diastolic blood pressure, TC Total Cholesterol, TG Triglycerides, LDL-C low Density Lipoprotein-C, HDL-C High Density Lipoprotein-C, ApoA1 Apolipoprotein–A1, ApoB Apolipoprotein B Yue et al. Lipids in Health and Disease (2017) 16:120 Page 7 of 8

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